7 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.CV2024
Cross-Modal Self-Supervised Learning with Effective Contrastive Units for LiDAR Point Clouds
Mu Cai, Chenxu Luo, Yong Jae Lee +1
3D perception in LiDAR point clouds is crucial for a self-driving vehicle to properly act in 3D environment. However, manually labeling point clouds is hard and costly. There has b…
cs.CV2023★ 1 cited
DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation
Zeyu Wang, Dingwen Li, Chenxu Luo +2
3D perception based on the representations learned from multi-camera bird's-eye-view (BEV) is trending as cameras are cost-effective for mass production in autonomous driving indus…
cs.CV2023★ 7 cited
PillarNeXt: Rethinking Network Designs for 3D Object Detection in LiDAR Point Clouds
Jinyu Li, Chenxu Luo, Xiaodong Yang
In order to deal with the sparse and unstructured raw point clouds, LiDAR based 3D object detection research mostly focuses on designing dedicated local point aggregators for fine-…